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Mathematical modelling of the MAP kinase pathway using proteomic datasets.

ABSTRACT: The advances in proteomics technologies offer an unprecedented opportunity and valuable resources to understand how living organisms execute necessary functions at systems levels. However, little work has been done up to date to utilize the highly accurate spatio-temporal dynamic proteome data generated by phosphoprotemics for mathematical modeling of complex cell signaling pathways. This work proposed a novel computational framework to develop mathematical models based on proteomic datasets. Using the MAP kinase pathway as the test system, we developed a mathematical model including the cytosolic and nuclear subsystems; and applied the genetic algorithm to infer unknown model parameters. Robustness property of the mathematical model was used as a criterion to select the appropriate rate constants from the estimated candidates. Quantitative information regarding the absolute protein concentrations was used to refine the mathematical model. We have demonstrated that the incorporation of more experimental data could significantly enhance both the simulation accuracy and robustness property of the proposed model. In addition, we used the MAP kinase pathway inhibited by phosphatases with different concentrations to predict the signal output influenced by different cellular conditions. Our predictions are in good agreement with the experimental observations when the MAP kinase pathway was inhibited by phosphatase PP2A and MKP3. The successful application of the proposed modeling framework to the MAP kinase pathway suggests that our method is very promising for developing accurate mathematical models and yielding insights into the regulatory mechanisms of complex cell signaling pathways.

SUBMITTER: Tian T

PROVIDER: S-EPMC3414524 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Mathematical modelling of the MAP kinase pathway using proteomic datasets.

Tian Tianhai T Song Jiangning J

PloS one 20120808 8

The advances in proteomics technologies offer an unprecedented opportunity and valuable resources to understand how living organisms execute necessary functions at systems levels. However, little work has been done up to date to utilize the highly accurate spatio-temporal dynamic proteome data generated by phosphoprotemics for mathematical modeling of complex cell signaling pathways. This work proposed a novel computational framework to develop mathematical models based on proteomic datasets. Us ...[more]

PMID: 22905119

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Project description:We investigated the relationships of the Cek1 and Cek2 mitogen-activated protein (MAP) kinases and the putative MAP kinase phosphatase Cpp1 in the mating process of Candida albicans Mutants of the CPP1 gene are hyperresponsive to pheromone, generating large halos, high levels of projections, and an increase in pheromone-responsive gene expression. Mating-type-homozygous opaque cells that lack both kinases are sterile, consistent with previous observations, although several lines of evidence show that the two kinases do not simply provide redundant functions in the mating process. Loss of CEK1 reduces mating significantly, to about 0.3% of wild-type strains, and also reduces projection formation and pheromone-mediated gene expression. In contrast, loss of CEK2 has less of an effect, reducing mating to approximately one-third that of the wild-type strain and moderately reducing projection formation but having little influence on the induction of gene expression. However, loss of Cek2 function reduces adaptation to pheromone-mediated arrest. The mutation enhances pheromone response halos to a level similar to that of cpp1 mutants, although the cpp1 mutants are considerably more mating defective than the cek2 mutant. The double cek2 cpp1 mutant shows enhanced responsiveness relative to either single mutant in terms of gene expression and halo formation, suggesting the kinase and phosphatase roles in the adaptation process are independent. Analysis of protein phosphorylation shows that Cek1 undergoes pheromone-mediated phosphorylation of the activation loop, and this phosphorylation is enhanced in cells lacking either the Cpp1 phosphatase or the Cek2 kinase. In addition, Cek1-GFP shows enhanced nuclear localization in response to pheromone treatment. In contrast, Cek2 shows no evidence for pheromone-mediated phosphorylation or pheromone-mediated nuclear localization. Intriguingly, however, deletion of CPP1 enhances both the phosphorylation state and the nuclear localization of Cek2-GFP. Overall, these results identify a complex interaction among the MAP kinases and MAP kinase phosphatase that function in the C. albicans mating pathway.IMPORTANCE MAP kinases and their regulators are critical components of eukaryotic signaling pathways implicated in normal cell behavior as well as abnormal behaviors linked to diseases such as cancer. The mating pathway of the yeast Saccharomyces cerevisiae was central in establishing the MAP kinase paradigm. Here we investigate the mating pathway in a different ascomycete, the fungal pathogen C. albicans In this dimorphic fungus MAP kinases are also implicated in the mating response, with two MAP kinases apparently playing redundant roles in the mating process. This work establishes that while some level of mating can occur in the presence of a single kinase, the Cek1 kinase is most important for mating, while the Cek2 kinase is involved in adaptation to signaling. While both kinases appear to be themselves regulated by dephosphorylation through the action of the Cpp1 phosphatase, this process appears important for mating only in the case of Cek1.

Dataset Information

Mathematical modelling of the MAP kinase pathway using proteomic datasets.

Publications

Mathematical modelling of the MAP kinase pathway using proteomic datasets.

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